| Space-based distributed radar has an excellent performance in longrange and slowly moving target indication.Space-based distributed radar system can obtain significant performance improvement in target speed estimation and positioning,through multi-satellite cooperative processing.Thus,it is of great significance and worth to the land,sea and air targets early warning and monitoring.Distributed multi-satellite formation systems have hybrid baseline for the most part,due to the constraint of the circular orbit geometry.Especially in the environment with great topographic fluctuation,the terrain interferometric phase introduced by cross-track baseline poses a significant challenge to clutter cancellation and moving target processing.For the terrain clutter,terrain interferometric phase leads to the clutter spectral broadening.And the clutter statistical distribution property is dependent of the range and height.Consequently,the terrain fluctuation clutter becomes nonhomogeneous,and clutter suppression becomes a significant challenge.For a moving target,the terrain interferometric phase introduced by the cross-track baseline is coupled with the phase of moving target caused by along-track baseline.This will result in estimation bias of traditional target velocity estimation methods that based on phase information,and the corresponding performance of moving target detection and parameter estimation will be deteriorated seriously.To overcome these difficult problems,this dissertation investigated the space-time distribution properties of terrain fluctuation clutter,texture structure of terrain interferometric phase,and the Doppler characteristics of moving target(or imaging position offset).Based on the above characteristics,we designed several algorithms,including clutter sample selection method,terrain interference phase compensation method,and moving target parameter estimation method,to improve the performance of distributed radar system under terrain fluctuation background.The main research works can be summarized as follows in this dissertation.1.For the wide area scan(WAS)detection mode,the problem of clutter spectrum broadening and the clutter heterogeneity caused by the disturbance of local terrain fluctuations,poses a significant challenge to clutter cancellation.To address this problem,we proposed a homogeneous sample selection method based on a novel concept of generalized spatial spectrum density function(GSSDF)and assisted by a priori DEM.This dissertation established the sample similarity measurement mechanism based on the characteristics of clutter spectrum distribution.Essentially,the core idea of the proposed algorithm is to select training samples data with similar clutter spectrum distribution,to perform local clutter suppression.First,the GSSDF is constructed by the prior information of digital elevation model(DEM)data,radar system parameters,and the backscattering model,to describe the spatial distribution properties of clutter echoes.Then,the angle of deflection(AOD)and the equivalent bandwidth(EBW)of GSSDF were adopted to measure the diffusion of clutter spectral.Finally,the criterion for homogeneous sample selection was established by a new threshold detection strategy,which combines the intrinsic relationship between null-notch of space-time adaptive filter and the characteristics of clutter spectrum(AOD and EBW).To summarize,this approach ensures that the training samples sharing similar clutter properties can be selected to estimate clutter covariance matrix(CCM),thereby improving clutter suppression capability under hybrid-baseline radar system configuration.2.To deal with the clutter suppression problem caused by the clutter range-elevation dependence in the mid-high resolution SAR imaging detection mode,we proposed a clutter suppression method based on iteratively adaptive compensation of terrain interferometric phase.This method can be summarized as a rough & refined two-step phase compensation framework.First,an adaptive terrain interferometric phase estimation method is designed based on the spatial texture structure of fringe morphology.The fringe direction and density are estimated using the gradient structure tensor.The slowly varying component of terrain interferometric phase is estimated as well as compensated using multi-baseline SAR image data.For refined topographic phase compensation,an error feedback weighting correction structure is designed to compensate for the fringe detail loss.The weighting coefficient is constructed based on coherence,phase residual distribution,and fringe structure features,which can be adapted to adjust the contribution of the phase estimation error.Moreover,to improve the topographic phase compensation performance,the proposed framework can be applied iteratively.Finally,clutter suppression was performed after the compensation of terrain interferometric phase.The experimental results demonstrate that the proposed approach has an outstanding performance of topographic phase compensation and effectiveness of clutter suppression.3.In hybrid-baseline radar system configuration,the problem of target elevation-speed coupling will result in the target radial velocity estimation bias.To address this problem,we proposed a target radial velocity estimation and relocation method based on the road network information assistance.First,the terrain interferometric phase of moving target is estimated by the clutter sample data.And the height-difference between imaging position and real position of target is compensated based on the prior road network information.Then,the target radial velocity can be estimated by adaptive matched filtering algorithm.Further,the radial velocity estimation and relocation results can be feedback to the target elevation compensation processing,iteratively.Finally,the experimental results of multi-satellite simulated data demonstrate that the proposed method can eliminate the impact of target elevation,as well as improve the performance of target velocity estimation and relocation in the observation scene with large topographic fluctuation. |
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